Note: Descriptions are shown in the official language in which they were submitted.
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AUTOMATED MANUFACTURING ARCHITECTURAL MILLWORK
BACKGROUND
[0001] There
are currently two basic market solutions for the production of
architectural millwork. These primarily include manufacturing units of pre-
determined sizes or
the production of custom units with less automated methods. While the first
method may be
more affordable, the realities of construction often require, at a minimum, a
combination of
both methods when units of fixed dimensions do not fit within the overall
dimensions of the
installation site, resulting in design and coordination costs that are
additional to the purchase
and basic installation of the units themselves. Designing solutions for
complex object and space
problems, such as the design and coordination of custom architectural millwork
in a space, may
involve the use of drafting and modeling software. Current software solutions
may require
considerable drafting expertise and familiarity with the design problem. The
time and skill
required to generate initial valid solutions for consideration with current
technologies may be
a significant barrier for access to custom architectural millwork products.
The design and
production of custom units without automated methods may be less affordable
than automated
methods, but may be of a higher quality. Therefore, it would be desirable to
develop an
automated design and manufacturing process for creating high quality, made-to-
order
architectural millwork with customizable dimensions and reasonable costs.
SUMMARY
[0002] A system
and method for making made-to-order architectural millwork of
custom dimensions; including the design of wood joints and a system for
deploying them
within the overall structural design of individual architectural millwork
units, as well as
methods for online design (including automated design aids) and ordering,
automated writing
of machine code, robotic part preparation, and simplified on-site
installation. With the
automation and generation of digital code for manufacturing custom
architectural components,
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this method makes the formation of distributed manufacturing centers possible.
Through this
method and with minimum re-tooling and/or training, these centers are able to
produce custom
millwork more efficiently and effectively than traditional custom millwork
woodshops.
BRIEF DESCRIPTION OF THE FIGURES
[0003] Advantages of embodiments of the present invention will be apparent
from the
following detailed description of the exemplary embodiments thereof, which
description
should be considered in conjunction with the accompanying drawings in which
like numerals
indicate like elements, in which:
[0004] Fig. 1 shows an exemplary diagram of process for making made-to-
order
architectural millwork of custom dimensions.
[0005] Fig. 2 shows an exemplary embodiment of a unit in the process.
[0006] Fig. 3 shows an exemplary embodiment of a unit with shelf in the
process.
[0007] Fig. 4 shows an exemplary embodiment of a set in the process.
[0008] Fig. 5 shows an exemplary embodiment of design aids in the process.
[0009] Fig. 6 shows exemplary edge types in the process.
[0010] Fig. 7 shows exemplary joint types in the process.
[0011] Fig. 8 shows an exemplary CNC Machine in the process.
[0012] Fig. 9 shows an exemplary unit assembly in the process.
[0013] Fig. 10 shows an exemplary installation in the process.
[0014] Fig. 11A shows an exemplary project and parameters of the process.
[0015] Fig. 11B shows an exemplary project and parameters of the process.
[0016] Fig. 12A shows an exemplary coded edge type of the process.
[0017] Fig. 12B shows an exemplary coded edge type of the process.
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[0018] Fig. 12C shows an exemplary coded edge type of the process.
[0019] Fig. 13 shows an exemplary diagram of distributed manufacturing with
the
process.
[0020] Fig. 14 shows an exemplary joint type of the process.
[0021] Fig. 15 shows another exemplary joint type of the process.
[0022] Fig. 16 shows another exemplary joint type of the process.
[0023] Fig. 17 shows another exemplary joint type of the process.
[0024] Fig. 18 shows an exemplary machine code generation diagram in the
process.
[0025] Fig. 19 shows an exemplary diagram for making preprogrammed
parametric
units in the process.
[0026] Fig. 20 shows an exemplary parametric part CNC geometry computation
in the
process.
[0027] Fig. 21 shows exemplary joints per edge relative to distances
between point
objects in the process.
[0028] Fig. 22 shows another exemplary joint type of the process.
[0029] Fig. 23 shows an exemplary panel with one edge type and two joint
types in the
process.
[0030] Fig. 24 shows an exemplary interior design product in the process.
[0031] Fig. 25A shows an exemplary building system product.
[0032] Fig. 25B shows an exemplary building system product.
[0033] Fig. 25C shows an exemplary building system product.
[0034] Fig. 25D shows an exemplary building system product.
[0035] Fig. 25E shows an exemplary building system product.
[0036] Fig. 25F shows an exemplary building system product.
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[0037] Fig. 25G shows an exemplary building system product.
[0038] Fig. 25H shows an exemplary building system product.
[0039] Fig. 251 shows an exemplary building system product.
[0040] Fig. 25J shows an exemplary building system product.
[0041] Fig. 25K shows an exemplary building system product.
[0042] Fig. 25L shows an exemplary building system product.
[0043] Fig. 25M shows an exemplary building system product.
[0044] Fig. 26 shows an exemplary embodiment of a joint type.
[0045] Fig. 27A shows an exemplary embodiment of a set with 2 layers.
[0046] Fig. 27B shows an exemplary embodiment of a set with 3 layers.
[0047] Fig. 27C shows an exemplary embodiment of a set with 4 layers.
[0048] Fig. 28 shows an exemplary embodiment of different sets.
[0049] Fig. 29 shows an exemplary embodiment of a set divided into maximum
and
minimum numbers of subsets.
[0050] Fig. 30 shows an exemplary embodiment of a set insertion function.
[0051] Fig. 31 shows an exemplary embodiment of a set deletion function.
[0052] Fig. 32 shows an exemplary embodiment of a set editing function.
[0053] Fig. 33 shows an exemplary embodiment of a set editing function.
[0054] Fig. 34 shows an exemplary embodiment of a set editing function.
[0055] Fig. 35 shows an exemplary embodiment of a set editing function.
[0056] Fig. 36 shows an exemplary embodiment of a set editing function.
[0057] Fig. 37 shows an exemplary embodiment of a set editing function.
[0058] Fig. 38 shows an exemplary embodiment of a set editing function.
[0059] Fig. 39 shows an exemplary embodiment of a set editing function.
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[0060] Fig. 40 shows an exemplary embodiment of a set editing function.
[0061] Fig. 41 shows an exemplary embodiment of a set editing function.
[0062] Fig. 42 shows an exemplary embodiment of a set editing function.
[0063] Fig. 43 shows an exemplary embodiment of a set editing function.
[0064] Fig. 44 shows an exemplary embodiment of a layout of a room.
[0065] Fig. 45 shows an exemplary method for generating a layout of a room.
[0066] Fig. 46 shows an exemplary embodiment of pre-programmed layout
types.
[0067] Fig. 47 shows an exemplary embodiment of a wall layout.
[0068] Fig. 48A shows an exemplary embodiment of a method for generating a
wall
design layout.
[0069] Fig. 48B shows an exemplary embodiment of a method for generating a
wall
design layout.
[0070] Fig. 49 shows an exemplary embodiment of a method for generating a
set.
[0071] Fig. 50 shows an exemplary embodiment of a method for generating a
wall
design layout.
[0072] Fig. 51 shows an exemplary embodiment of a method for automatically
generating set designs.
[0073] Fig. 52 shows an exemplary embodiment of different sets with
individual fitness
scores.
[0074] Fig. 53A shows an exemplary embodiment of a set generator function.
[0075] Fig. 53B shows an exemplary embodiment of a set generator function.
[0076] Fig. 54 shows an exemplary embodiment of an input and an output of a
set
editing function.
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[0077] Fig. 55
shows an exemplary embodiment of a method for solving a design
problem.
DETAILED DESCRIPTION
[0078] Aspects
of the invention are disclosed in the following description and related
drawings directed to specific embodiments of the invention. Alternate
embodiments may be
devised without departing from the spirit or the scope of the invention.
Additionally, well-
known elements of exemplary embodiments of the invention will not be described
in detail or
will be omitted so as not to obscure the relevant details of the invention.
Further, to facilitate
an understanding of the description discussion of several terms used herein
follows.
[0079] As used
herein, the word "exemplary" means "serving as an example, instance
or illustration." The embodiments described herein are not limiting, but
rather are exemplary
only. It should be understood that the described embodiments are not
necessarily to be
construed as preferred or advantageous over other embodiments. Moreover, the
terms
"embodiments of the invention", "embodiments" or "invention" do not require
that all
embodiments of the invention include the discussed feature, advantage or mode
of operation.
[0080] Further,
many embodiments are described in terms of sequences of actions to
be performed by, for example, elements of a computing device. It will be
recognized that
various actions described herein can be performed by specific circuits (e.g.,
application specific
integrated circuits (ASICs)), by program instructions being executed by one or
more
processors, or by a combination of both. Additionally, these sequences of
actions described
herein can be considered to be embodied entirely within any form of computer
readable storage
medium having stored therein a corresponding set of computer instructions that
upon execution
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would cause an associated processor to perform the functionality described
herein. Thus, the
various aspects of the invention may be embodied in a number of different
forms, all of which
have been contemplated to be within the scope of the claimed subject matter.
In addition, for
each of the embodiments described herein, the corresponding form of any such
embodiments
may be described herein as, for example, "logic configured to" perform the
described action.
[0081]
According to an exemplary embodiment, and referring to the Figures generally,
a system and a method of an automated manufacturing architectural millwork may
be
described. According to an exemplary embodiment, such a system and method may
produce
higher quality architectural millwork with greater storage space and custom
dimensions at a
competitive price. Increased structural integrity of the product may be
achieved with the design
of wood joints and a system for deploying them within architectural millwork
units. Millwork
units with custom dimensions may be efficiently created through the process of
automatically
computing machine code for robotic part preparation. As a result, custom
architectural products
may be produced with efficiencies similar to mass production of units of
standard shapes and
sizes. The manufacturing may be distributed into a network of regional centers
(potentially in
coordination or in partnership with existing third-party shops); realizing
efficiencies in
transportation costs and allowing the company to scale and adapt to changes in
market demand
more easily than centralized manufacturing centers. Also, the ability to fully
automate custom
part fabrication from custom design parameters, may create greater
efficiencies through the
creation and practical application of automated online customer-driven design
tools.
[0082]
According to an exemplary embodiment, a manufacturing process may be
automated creating high quality, made-to-order architectural millwork with
customizable
dimensions. Such a process may be applicable to millwork constructions
including but not
limited to cabinets, shelves, free-standing closets, credenzas, storage boxes,
and vanities as
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desired. In comparison to conventional industry mass production methods, the
automated
manufacturing process may have a number of benefits. For example, it may
eliminate manual
cutting and measuring during the creation of dimensionally variable millwork
and it may enable
the integration of efficient customer-driven design and installation
techniques.
[0083] In
addition, the product may have structural benefits in comparison to
conventional solutions. Reproducing proposed designs for connecting parts may
be time
consuming, require highly- skilled carpentry and may be cost prohibitive with
conventional
made-to-order methods. The design of these connections as well as the methods
for integrating
them into a mass production process with machine precision may provide for a
product of
greater strength (more durable) while using less material (more storage
space).
[0084] Turning
now to exemplary Figs. 1, 2, 3, 4 and 5, Fig. 1 may show an exemplary
diagram of a process 100 for making made-to-order architectural millwork of
custom
dimensions. According to an exemplary embodiment, the process may include five
major
phases: design 110, review 120, ordering 130, manufacturing 140 and
installation 160. In an
exemplary embodiment, the development of a millwork product may begin as a
customer-
initiated project and ends with the delivery of a coordinated set of custom
millwork units for
installation. Also, in an exemplary embodiment, the process may provide a web-
based
interface, and it may allow the customer to drive the design process, and
software may generate
data and documentation for ordering, manufacturing, shipping and installing
the millwork
product. Such a process may provide opportunities to reduce overall labor,
time, error and costs
in comparison to conventional practice.
[0085] The
process 100 may start with an option to either begin the design phase 110
or repair interface 102. The design interface 112 may present an intuitive
user interface. The
user may then design the project 114 using the user interface which may supply
the user with
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design aids. In a next exemplary step, the user may enter project parameters
116 (see Fig. 11
for an example of project parameters), such as desired dimensions.
[0086] Next,
the review phase 120 may begin. In a first exemplary step of the review
phase 120, the software may model the user's project 122. Then, the project
may be viewed
124. The customer may view the project as a web-based 2D and/or 3D
representation. Further
embodiments may allow the customer to view virtual reality and augmented
reality formats.
Some customers may be wary of how a piece of furniture looks on the intern&
and may instead
seek to view the product in person. Virtual reality and augmented reality may
allow a customer
to view the project as if it is in their room or right in front of them. The
customer may view the
project in its entirety, including all sets and units, as well as each unit
individually within one
frame. By isolating the sets or units, the software may facilitate the use of
design aids for
adjusting parameters such as dimensions and alignments. The customer may then
download
the custom digital models of the project as computer-aided design (CAD) files
in 2D and 3D
formats. This may facilitate the coordination of larger projects which the
units or sets may be
integrated with. In a further exemplary embodiment, scaled 3D models may be
downloaded in
a format for 3D printing. In another exemplary step of the review phase 120,
the customer may
view project data 126. Project data may include information for final review
and approval
before ordering, such as descriptions of each unit and project costs.
[0087] In a
next exemplary phase, the product may be ordered 132 to begin the ordering
phase 130. Once the customer places an order 132, the software may process the
order 134. In
processing the order 134, the software may save the order to an online account
and may also
generate assembly data, installation data, order shipping data, order tracking
data, drawings,
models, and instructions for reference to facilitate with the assembly 156 and
installation 160.
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[0088] After
the ordering phase 132 has been completed, the manufacturing phase 140
may begin. In a first exemplary step of the manufacturing phase 140, the
manufacturing data
may be computed 142. The manufacturing data may be further illustrated in Fig.
18. The
manufacturing data may produce the material list 144, generate the machine
code for directing
the cutting, routing, etching, milling, sawing, bending, forming, welding,
pinning, gluing,
taping, sanding, painting, finishing, holding, conveying, picking and/or
placing machine
operations (such as for a CNC machine) 146, may provide assembly data 148, and
may provide
data to facilitate the installation process. Exemplary assembly data may
include data for
tracking parts, orienting parts, assembling parts in order, picking parts,
holding parts,
conveying parts, joining parts, cataloging unit hardware, identifying unit
hardware locations,
installing unit hardware, picking units, holding units, conveying units,
finishing units,
packaging units, and cataloging unit adjacencies. Examples of data used to
facilitate the
installation process may include data for identifying unit locations within an
overall designed
space (such as a kitchen where the physical units are compared to
visualizations of units of
automatically generated physical drawings or automatically generated drawings
and models
visualized on a personal computer or augment reality device), identifying
peripherals of a unit
that may require separate packaging and on-site assembly, and providing on-
site installation
instructions (such as unit installation sequence). The assembly data may be
delivered to the
manufacturing center through various methods as static or interactive text,
drawings and
modeled illustrations.
[0089]
Exemplary visualization formats may include automatically generated labels for
part identification, orientation, assembly order, and part adjacency indices.
These labels may
be automatically printed and temporarily adhered to parts manually or
automatically with a
robotic apparatus. More complex data and instructions may be delivered to the
manufacturing
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center as programs for augmented reality devices or any other type of
graphical user interface.
Augmented reality models (or models viewed on other computing devices such as
a personal
computer or mobile device) and visualizations may provide access to assembly
data, and may
provide the manufacturer with the information needed to complete the task
within a single
program designed for the assembly of a unit or units. This may allow the
company to create
programs that automatically design and deliver a model for a custom unit to
the manufacturer
irrespective of the manufacturer's level of experience assembling like units.
Some
manufacturers may use the model to access a limited amount of information,
while other
manufacturers may use the same model to access more information, thus
increasing their
confidence in the ways in which they are assembling the units. The training
manual for all
levels of experience may be imbedded in the assembly data for any given unit.
This may
minimize errors in the assembly process as new manufactures become familiar
with the
manufacturing process.
[0090] Assembly
data may also be delivered electronically to programmable
apparatuses at the manufacturing center to assist in the shaping, assembly,
convey, sorting, and
shipping of parts and units, such as carts with electronic displays.
Identifying, sorting, and
tracking parts may be a considerable challenge with custom units, where every
part of a project
order is unique. Programs may be created for the carts, where the display
panels may be
associated with slots or containers of the carts, and may indicate locations
for placing parts
with unique identification markings corresponding to markings on the display
panels of the
carts. When parts are removed from the holding apparatus of a CNC machine or
assembly
station, they may be quickly placed in containers or slots of the carts. The
program may direct
the positions of each part in the cart so that they may be quickly and
sequentially picked from
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the cart to be placed in another CNC machine holding apparatus or assembled in
order. For
example, a cart may contain parts for two units of a project.
[0091] The
parts in the cart could be arranged so that the manufacturer may quickly
pick from the cart parts for the first unit in the order by which they are
assembled, followed by
parts of the second unit in the order by which they are assembled. The cart
can then be re-
programmed for parts of other units or for sorting and delivering assembled
units to another
manufacturing station, such as a finishing station. The software may then use
the material list
to order the material for the project 150, as previously calculated 142. An
example of material
used in the process is stock material pre-processed to industry standard
sizes, such as sheets of
wood, boards of wood, sheets of foam, sheets of metal, sheets of plastic,
sheets of glass, pipes,
tubes, and other metal and plastic extrusions.
[0092] In a
next step, the material may be delivered from the supplier to the shaping
location 152. At the shaping location, the material may be shaped 154, for
example, using a
CNC machine or by other means. Examples of part shaping may include cutting,
routing,
milling, forming, bending, and sawing. After shaping, the shaped material may
then be
assembled 156. The shaped material may then be finished 158, such as by
sanding, staining,
and painting the assembled units. The material may be finished before shaping,
after shaping,
or not finished at all.
[0093] The
final phase may be the installation phase 160. The product may be shipped
from the cutting and assembly location to the install location 162.
Alternatively, the product
may be stored at a regional manufacturing center or at another storage center
for convenient
pick-up. In a final step, the customer may install the units 164.
[0094]
Referring now to Figs 2, 3, 4 and 5, Fig. 2 may show an exemplary embodiment
of a unit in the design process. The 'w', 'd', and 'h' denoted in Fig. 2 may
represent the width,
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depth, and height of the desired object. A customer may enter parameters to
specify the width,
depth, and height, or a set of recommended specifications may be used. In
exemplary Fig. 3,
an exemplary embodiment of a unit with a shelf selected in the design process
may be shown.
In addition to the global parameters shown in Fig. 2, each unit may have
internal parameters
for adding shelves, drawers, doors, etc. Referring now to Fig. 3, the shelf
may be selected,
moved, or removed. Further, the shelf may be copied, and an additional
identical shelf may be
placed on the design. Fig. 4 may show an exemplary embodiment of a set in the
design process.
The set in Fig. 4 may be aligned such that they are of equal heights and
depths. If the units are
configured to be combined as an interconnected set, the interior walls 202 may
be unfinished
and may be fitted with a joint or other means for connecting the two walls.
[0095]
According to an exemplary embodiment, the process may begin with the design
phase, which may include customer-driven design using pre- programmed
elements. In an
exemplary embodiment, the customer may initiate a project which is defined as
unit(s) and/or
set(s) of units (shown in Fig. 11 A) rendered in a web based three-dimensional
graphical user
interface. Fig. 5 may show an exemplary embodiment of design aids in the
design process.
Each unit may be added to a web based three-dimensional model at a default set-
out position,
a customer defined set of coordinates (x, y, z) relative to an origin or
object already positioned
in the model, or by associating one side of the added unit to a selected side
of a unit already
positioned in the model, forming a set as shown in Fig. 4 and Fig. 5.
According to an exemplary
embodiment, the forming of sets may allow the software to catalog adjoining
units. There is
no limit to how many adjoining units exist in a single set. This information
may be used to
generate custom documentation and connections that simplify the installation
process.
[0096]
According to an exemplary embodiment, other design aid features of the
graphical user interface may include functions for aligning and setting units
of equal sizes as
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shown in Fig. 5. In an exemplary embodiment, the aligning function may
facilitate the
alignment of two or more sides with parallel planes by identifying a target
plane. For each
manipulated unit, the function may compute a value that either increases or
decreases its overall
dimension that is perpendicular to the target plane. Also, in an exemplary
embodiment, another
function may re-compute vector parameters of equal value for selected units,
such that the
directions of the parameters are parallel, and their sum value is client
defined.
[0097]
According to an exemplary embodiment, at the conclusion of the design phase,
the review phase may begin. The system may compute and render two-dimensional
and three-
dimensional computer-generated visualizations, a list of project parameters
(such as types of
units, dimensions, numbers of doors/drawers/shelves), and the project cost.
Optionally, the
customer may download these representations as files readable by computer
aided design
software for integration into the design of larger projects requiring greater
coordination. The
parameters of projects may be saved as closed proprietary specifications for
builders. If the
customer accepts, the order processing phase may begin. In an exemplary
embodiment, order
processing may be executed by software that takes the design parameters for
each unit as inputs
and outputs lists of machine instructions for the automated cutting of parts
in preparation for
the manufacturing phase. The machine instructions may include details such as
the height and
width of each piece, the number of pieces, and the shapes of each piece. The
pieces may be cut
into rectangular shapes. The edges of the pieces may be cut to form a
protuberance or aperture
to join such that the edge of one piece may join with the edge of another.
[0098]
Referring now to exemplary Figs. 6 and 7, different exemplary joint types and
edges may be shown. Each unit may be a programmed set of surfaces and edge
types. As
shown Figs. 6 and 7, each edge type may be a set of joints. Any type of joint
or combination
of types of joints may be contemplated. Fig. 6 may illustrate the application
of various joints
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mortise and hammer-headed tenon joints 602, mortise and tenon joints 604,
splice joints 606,
and mechanical fasteners 608. One or more mortise and hammer-headed tenon
joints 602 may
be used to join the edges or corners of two pieces at a 900 angle. One or more
mortise and tenon
joints 604 may join the edge or corner of one piece to an interior portion of
another piece. One
or more splice joints 606 may join the corner or edge of one piece to the
corner or edge of
another piece such that the two pieces run along the same plane to form one
flat piece.
Additionally, one or more of mechanical fasteners may join two pieces which
may be stacked
on top of or next to each other such that their surfaces are parallel and
connected.
[0099] Fig. 7
may show various methods for joining two planar parts of wood. A
ninety-degree corner 702 may be formed using a process similar to dovetail
joinery where the
edges of the two parts interlock. A T-shaped connection where the edge of one
piece connects
with a center or interior portion of another piece 704 may be formed by
creating an aperture in
the interior portion of one piece and a correspondingly sized protuberance on
the edge of
another piece. Further, a splice joint 706 may connect two planar parts of
wood of different
thicknesses such that they run along the same plane in the same direction,
with one piece
extending out from the end of the other piece. Additionally, Fig. 7 may also
show a method of
joining two planar and parallel pieces where one part may have an embedded
insert nut 708
and may connect to another part which has a screw 710 which engages the nut
708. Various
other types ofjoints may be implemented into the pieces, such as dovetail or
tongue and groove
joints.
[0100] The
number ofjoints and the spacing between each joint (shown in Fig. 21) may
be formulaically calculated from parameters defined in the design phase.
Software may
compute machine code for all joints and parts required to construct each unit
from flat sheets
and/or boards of non- metal material (such as plywood and solid hardwood).
Parts may be
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algorithmically arranged in a two-dimensional plane with x and y lengths
equivalent to sizes
of physical material to be machine cut (This function may be called nesting).
Software may
then output machine readable digital files for a computer numerical control
(CNC) routing
machine, as shown in Fig. 8.
[0101]
Referring now to exemplary Fig. 8, a CNC routing machine may be shown. The
CNC machine may have a router 802 which may be the main cutting element. The
router 802
may spin and may be fitted with a cutting surface. The router 802 may be
connected to a number
of rails which may allow the router to move anywhere along the flat bed 804 of
the CNC
machine. A sheet of material to cut 806 may be placed on top of the flat bed
804, such that the
router may cut any part of the material 806. Multiple parts 807 may be cut
from a single sheet
of material 806. A fixed x-axis rail 808 may be affixed to a side of the CNC
machine. A y-axis
rail 810 may be perpendicularly connected to the x-axis rail 808, allowing the
y-axis rail 810
to move along the x-axis rail 808. A z-axis armature 812 may be movable
connected to the y-
axis rail 810, such that the z-axis armature 812 can slide in any direction
along the y-axis rail
810. Since the y-axis rail 810 can additionally slide along the x-axis rail
808, the z-axis
armature 812 may be moved to anyplace along the plane of the flat bed of CNC
machine, in
the x and y direction. Further, the z-axis armature 812 may move in a vertical
direction, down
towards the flatbed 804 and material to be cut 806. In this example, the
apparatus for holding
the material may be a flat vacuum table 804. Examples of other CNC machines
include
machines that have an apparatus for holding material and numerically
controlling the motion
of a tool for shaping parts, including subtractive and additive manufacturing
tool heads, of
various material types, such as the parts shown in Fig. 25. The material
holding apparatus may
also be numerically controlled, and capable of moving the held material in the
x-axis, y-axis,
z-axis, or any combination of the three, while handling or shaping material.
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[0102] After
cutting, the parts may be unloaded from the machine bed and assembled.
Each part may have an identification tag indicating the unit type and its
place within the
assembly sequence as shown in Fig. 9. Adjoining parts may be held together
with glue and
friction. Lack of rigidity is a common critique of manufactured millwork. This
is typically
overcome through the use of heavier duty mechanical fasteners and thicker,
higher quality
materials. The interlocking joinery of the proposed method may yield superior
rigidity with
material of minimal thicknesses, reducing potential time lost in sending back
damaged units
while increasing the storage area available to the client. Parts may be
assembled with a single
tool, such as a mallet and a simple technique, such as hammering. Because the
complex cutting
may be computed by the software and performed by the CNC machine, fewer labor
skills are
required to assemble custom sized millwork of superior quality and rigidity.
[0103]
Referring now to exemplary Fig. 10 and Fig. 11, the assembly of a set may be
shown. As shown in Fig. 10, a set 1000 may be a combination of a plurality of
products. (For
example, a given set 1000 may include a unit 1002 having a door which itself
constitutes a unit
1004, or may include a cabinet which operates as a unit 1002 defined within
another unit 1004,
such as a row or column of cabinets.) Unit 1002 and unit 1004 may be similarly
sized in the
design phase such that they may be placed next to each other as a single unit.
Mechanical
fasteners may be used to join the first unit 1002 and the second unit 1004. As
shown in Fig. 10
and Fig. 7, the mechanical fasteners may be a screw 710 in a first unit 1002
which engages a
correspondingly placed nut 708 in the second unit 1004. Multiple mechanical
fasteners may be
used, depending on the size or structure of the units. In an exemplary
embodiment, the first unit
1002 and the second unit 1004 may have equal heights and depths.
[0104] Fig. 11A
may show an exemplary embodiment of wall mounted cabinets 1100.
The cabinets may be a combination of multiple units. In this exemplary
embodiment, a double
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cabinet 1102 is joined with a single cabinet 1104. They may be joined by an
adhesive, screws
and nuts, or by any other technique. Further, a leveling platform 1106 may be
placed under the
joined units 1102 and 1104. The leveling platform 1106 may be fixedly attached
to the units
and may also be fixed to a wall.
[0105] Fig. 11B
may be an exemplary embodiment of unit parameters related to the
exemplary cabinet unit in Fig. 11A. The design software may record these
parameters
according to a user's specifications, or some of them may be automatically
populated by the
software. Possible parameters that may be recorded include the type of unit,
width, height,
depth, number of peripherals, and adjacencies. The type of unit may be a
specific style or may
refer to the position or place it is to be mounted. The number of peripherals
may include doors,
shelves, windows, or other fixtures that may be mounted or attached to the
furniture. Further,
the width, depth, and/or height of each peripheral may be included. The
adjacencies parameter
may include information about which units may be directly adjacent or attached
to the unit
being described.
[0106] For
example, in Fig. 11A the double cabinet 1102 is adjacent and attached to
the cabinet 1104, so an exemplary adjacency parameter for cabinet 1102 may
contain
information defining the side which cabinet 1104 is attached to, such as the
left side, and the
method of attachment, which in this exemplary case may be screws and nuts.
Another
adjacency parameter for cabinet 1102 may define the leveling platform 1106 on
the bottom of
cabinet 1102 and may implement a screw/nut method of attachment. In another
exemplary
embodiment, the method of attachment may be an adhesive, or any other
attachment method
such as may be desired. Further, the adjacency information may be stored or
viewed in the form
of an adjacency graph 1110. The adjacency graph 1110 may show which items are
attached to
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one another as well as the location of their attachment. Additionally, the
adjacency graph 1110
may store edge type information.
[0107] In an
exemplary embodiment, edge type information may be stored in a 3D
model of the unit, with the edges denoted by an edge type symbol, as shown in
exemplary Fig.
12A. In exemplary Fig. 12A, an edge may be denoted by an 'e', and the type of
edge may be
denoted by the subscript under the e. For example, e2B may represent a mortise
shaped edge
that may be configured to join a corresponding tenon shaped edge represented
as e2A. In this
exemplary embodiment, the edges may instead be represented by actual drawings
of the
contemplated edges, as shown in Fig. 12B. The assembled unit 1200 may be a 3-
dimensional
model which illustrates all the edges and the corresponding joints created.
[0108]
Referring now to exemplary Fig. 12C, an illustration of the edge types of a
unit
may be shown. The software may automatically compute the location and type of
edges for
each piece. The edge information may then be saved in a format that is
readable by a CNC
machine. The CNC machine may then cut and drill the parts. As a result, the
amount of manual
labor, such as cutting, drilling, or measuring the parts, may be reduced.
Additionally, the edge
profile of certain parts, such as the horizontal piece 1202 in Fig. 12C, may
follow the inside
surface of door 1204, and may run along a portion of door 1204 which is made
thinner in order
to receive the horizontal piece 1202, thus maximizing storage space. In
addition to structural
rigidity, the edge detail may produce an inlay appearance, such as when two
edges are
composed of different materials.
[0109] The
automation of manufacturing data (CNC machine code, assembly
instructions, and associated project metadata) from customer defined
parameters for custom
millwork may enable the practical implementation of a distributed
manufacturing network
shown in Fig. 13. The customers 1302 may place orders by utilizing the design
interface 1304.
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The design interface 1304, as previously discussed, may receive customer input
and then may
compute manufacturing data 1306. The manufacturing data 1306 may be in the
form of code
readable by a CNC machine. The data 1306 may then be sent to a manufacturing
center 1308.
Additionally, the software may also order materials needed or send a list to
the manufacturing
center specifying the materials needed. Alternatively, the software may send
bills of materials
to centers. In another exemplary embodiment, the materials may be cut at one
manufacturing
center 1308 and then sent as flat-packed parts to centers closer to the
customer for assembly
and finishing. The manufacturing center 1308 may be chosen based on the
customer's location.
[0110] By
selecting manufacturing centers 1308 located close to the customers 1302
placing orders, there may be reductions in transportation and energy costs and
representatives
from these centers may more easily supply on-site assistance with the pre-
order and post-
delivery phases. Additionally, the business may be able to develop contracts
with existing
regional shops already in possession of the skilled labor and/or machinery
required for
executing the orders. Alternatively, the company may contract the assembly
with a third-party
shop and supply the shop with flat-packed parts from a separate robotic
cutting facility or
facilities. With minimum re-tooling and/or training in the manufacturing
methodology and
techniques, these shops may gain access to a larger market for custom millwork
and may
complete the work without the challenges associated with drafting, measuring,
cutting custom
parts, or describing design limitations to customers. In return, the business
may gain rapid
scalability and resilience to changes in market demand. The company may be
able to develop
units and sets of other types of architectural products of various materials,
by designing new
pre-programmed units and engaging shops with other types of CNC equipment such
as
programmable laser-cutters, water-jet cutters, and five axis machines with
custom tool heads.
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[0111] A
customer 1302 may also select a preferred regional manufacturing center
1308 if desired. Representatives from a manufacturing center 1308 may be
available to provide
services such as direct assistance during the design or installation phase.
For example, a
representative from the manufacturing center may provide a local installation
team that can
install the units, or the center itself may employ one or more specialists who
can install the
units or sets. The representatives may assist customers with on-site
measurements, design
selection, and configurations. Further, the manufacturing center 1308 may have
display models
of already manufactured units or sets that a customer may choose to see prior
to purchasing or
designing their own unit.
[0112] The
project may be shipped to the customer as ordered set(s) of units for the
installation phase. Unit identification tags correspond to the units shown in
the project web-
based design model and the installer may refer to this model as an
installation aid. With the
pre-fabricated threaded inserts and pre-drilled holes for machine screws, for
example, as shown
in Fig. 6, "e4", the installer may rapidly and accurately align units within
set(s) as shown in
Fig. 10. It is relatively time consuming to utilize these types of fasteners
with conventional
custom millwork methods and it is impractical with standard manufactured units
that are
designed and built with no reference to specific adjoining units. On the other
hand, in
exemplary embodiment, the ability of the software may map the adjacencies
within a set of
units and translate that information into machine code that accurately
positions the fasteners
enabling the effective use of this fastener
[0113] Also, in
exemplary embodiment, project data may be saved in an online account
for reordering parts for repairs. A mechanical fastener solution, for example,
as shown in Fig.
7 "j4" may facilitate easy replacement of new parts without residual damage to
adjoining parts
from the use of typical on-site unit alignment solutions (ex- nails and wood
screws).
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[0114]
Referring now to the exemplary embodiment in Fig. 14, a mortise and hammer-
headed tenon joint may be shown. This type of j oint may be implemented when
two pieces are
connected at a 90 angle. The letters on part A of Fig. 14 correspond with the
letters on part B
of Fig. 14, such that the same letter indicates the same length on both parts.
The hammer-
headed tenon 1400 may be shown on part A as a tenon with a neck 1402 and a
thicker head
1404. The head 1404 may be sized such that it may be received by the upper
portion 1414 of
the notch 1410. The lower portion 1412 of notch 1410 may be thicker than the
upper portion
1414 such that it may contact the neck 1402 of the tenon. Note that in this
exemplary
embodiment, the tenon 1400 is configured such that it must be vertically
connected to a
horizontal mortise 1410, however other configurations are contemplated.
[0115]
Referring now to the exemplary embodiment of a joint in Fig. 15, a mortise and
tenon joint may be shown. A rectangular tenon 1502 on a first part 1500 may be
sized such that
it may enter a rectangular aperture or mortise 1504 in a second part 1510. The
advantage to the
mortise and tenon configuration is that the mortise may be placed anywhere
along the second
part, such as in a middle portion. A mortise and tenon joint may be used to
affix shelves, walls,
or any other fixtures to a unit.
[0116]
Referring now to the exemplary embodiment of a joint in Fig. 16, a splice
joint
may be shown. A small rectangular mortise 1602 on a first part 1600 may
receive a
correspondingly sized tenon 1612 on a second part 1610. Additionally, a hammer
headed tenon
1604 on the first part 1600 may contact a correspondingly shaped mortise 1614
on the second
part 1610. Further, a groove 1606 on the first part 1600 may receive a bump
1616 on the second
part 1610. The two parts may be joined such that they run along the same plane
and extend
from one another. By applying multiple types of connections, such as a hammer-
headed tenon,
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a groove, and a rectangular tenon, the joint may be more stable than
traditional joints that only
use one type of connection.
[0117]
Referring now to exemplary Fig. 17, mechanical fasteners may be shown. A
threaded insert nut 1702 may be installed in a first part. The nut may be
inserted into a CNC
drilled hole 1704. The second part may contain a correspondingly placed CNC
drilled hole
1706. A screw may be inserted into and through the hole 1706 in the second
part until the screw
contacts and threads with the nut 1702 placed in the hole 1704.
[0118]
Referring now to exemplary Fig. 18, a machine code generation diagram may
be shown. The process for generating the CNC machine code begins with the
default unit
parameters 1802. The customer may choose a unit, and the software may provide
sample unit
parameters 1802. The customer may then assign parameters to the unit 1804 as
desired. Once
the parameters are finalized, the software may define a unit object 1806,
which may be a single
unit or product. An object as described in this section may be a 2D or 3D
computer aided design
object. In a next step, the unit object may be further analyzed to create or
compute one or more
part objects 1808. The part objects may correspond to the different pieces of
the unit, such as
the walls, panels, or shelves. When the part objects are computed 1808, each
part's CNC
geometry 1810 may be produced, including their edges and sizes. Fig. 20 may
further describe
the computation of CNC geometry. In a next step, the software may apply a
nesting algorithm
1812 to nest the part CNC objects, producing a nested CNC geometry 1814. The
nesting
algorithm may optimize the CNC geometry such that a minimal amount of material
is wasted
when the parts are cut from sheets. The nested CNC geometry may then be
written or saved as
a CNC file 1816. The CNC file is then sent to a desired manufacturer 1818. The
manufacturer
may place a material, such as a wood sheet, on a CNC bed 1820. Finally, the
CNC file
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previously written is run on the CNC machine 1822, cutting the wood sheet as
calculated and
modeled by the part object geometry.
[0119]
Referring now to exemplary Fig. 19, Fig. 19 may illustrate how a unit object
is
computed. First, the user (such as a customer or company) may design or sketch
a new unit
1902 through a design interface. The design interface may present an intuitive
interface and
may be web-based. In a next step, the software may determine the type of edges
to be used
1904 as well as which objects contain edges 1906. The software may determine
the lengths of
the edges of each part (as determined from the unit parameters such as the
height, depth, and
width) 1908. The lengths and orientations of the edges of each part may be
stored as vectors
1910. The vectors may then be used to model parametric points of two or three
dimensions
1912 in order to generate toolpath data for each part for shaping (cutting,
etching, routing,
milling, sawing, bending or forming) with a CNC machine. The data from the
vectors, point
objects, unit parameters, edge types, and edge objects may be compiled in
order to compute a
single unit object 1914. The unit parameters may be defined as value ranges
rather than discrete
values, and the unit object may be stored in computer memory to generate
multiple custom
units of a similar type with minimal inputs (simply declaring unit parameters
with pre-
programmed value ranges).
[0120]
Referring now to exemplary Fig. 20, Fig. 20 may illustrate the sequence of CNC
geometry computations, as explained in Fig. 19. V1-3 may illustrate vectors
that represent the
length and orientation of a single edge of apart. P1-6 may be different point
objects which may
define the start points, end points, and adjacencies of the edges. For
example, the first edge
with start point Pi and end point P3 may be adjacent to the second edge with
start point P3 and
end point P4 (the end point of the first edge is the same as the start point
of the second edge).
The coordinates of points P2-6 are calculated from an origin point Pi after
the part parameters
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are defined. In this example the length of V3 may be equal to the width of a
unit, while the
length of Vi may be equal to the height of a unit. From a catalog of edge
types with their own
sets of vectors, points, edges, and joint types, toolpath data for the part
may be generated and
compiled into a CNC file. The CNC machine may then shape the desired edges and
joints
according to the given CNC file.
[0121]
Referring now to exemplary Fig. 21, the number of joints per edge relative to
distances between point objects may be shown. A longer edge 2102 may have more
joints per
edge than a shorter edge 2104. The software may compute the number ofjoints
per edge based
on the distance between point objects.
[0122]
Referring now to exemplary Fig. 22, Fig. 23, and Fig. 24, a corner joint type
may be shown. A slanted mortise 2202 on object 2200 may receive a slanted
tenon 2212 on
object 2210. Fig. 23 and Fig. 24 may show an example panel with the corner
joint. The corner
joint may be implemented in a unit with any number of sides and variable
angles between
adjoining sides, as shown in Fig. 24. Using the same process previously
described and outlined
in Fig. 1, a picture frame such as the ones shown in Fig. 24 may be created.
The customer may
choose any desired number of sides, shapes, or sizes for the picture frame.
Additionally, the
CNC technology may enable the integration of custom engravings into the face
of the frame
material.
[0123] With the
processes outline in Figs. 1, 18, and 19, a customer may use a web-
based user-interface to design digital surfaces by positioning point objects
and declaring edge
objects in a 3D graphical user interface. The customer may use functions of
the interface for
joining surfaces as one or more sets. The software may compute the
intersection of these
surfaces and render the result in the 3D graphical user interface. Other
customer input
parameters may include building system types. These inputs may be referred to
as design
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inputs. Various design inputs may allow the software to compute manufacturing
data from pre-
programmed and parametric unit objects. Unit objects may include structural
units, such as in
Fig. 25B, sheathing units such as in Fig. 25H, and formwork units as in Fig.
251. An advantage
of these processes and pre-programmed units may be shown in Fig. 25. These
processes and
pre-programmed units allow a customer to construct complex geometric
architectural form
while minimizing the amount of manual measuring, cutting, or assembling
necessary, thus
reducing the time and labor necessary to complete such a task.
[0124] The term
"set of structural units" may refer to an ordered set of structural units.
For example, Fig. 25B may show a set of structural units. The structural units
in this figure
form a complex doubly curved surface. The surface may have u- and v-
coordinates that
correspond to x- and y- coordinates of a flattened design surface. The
flattened design surface
may be a network of sets, like the network of sets illustrated in Fig. 27. For
instance, a low
level set within the network may be the combination of regions el and e2 in
Fig. 25B, where
the combination of these regions has a width and a height parameter.
Similarly, regions cl and
c2 may represent a set, and regions al and a2 may represent another set in
Fig. 25B. These
three sets may be grouped in another set to form a column. Prior to generating
CNC
manufacturing data for the units, unit and part edge point locations as well
as vector lengths
and orientations may be calculated by mapping these coordinates from the x-
and y- coordinate
system of the flattened design surface to the u- and v- coordinate system of
the three-
dimensional design surface. Fig. 25C may show a single structural unit. The
structural unit in
exemplary Fig. 25C may be a set of assembled parts. In this exemplary case,
the unit is a
triangle formed from round tube, flat plates and mechanical fasteners. An
alternative to the
mechanical fasteners may be welded connections performed by a CNC welding
machine. A
structural unit may be composed of various materials, such as round tubes or
flat plates which
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may be cut from stock material using a CNC machine. Fig. 25D may show a
section through
corner connection of a structural unit. Fig. 25E may show the connection
between two
structural units, creating a set. Fig. 25F may show a cross-section of a
connection of two
structural units. The angle between the two units may vary and may be
calculated from
customer defined inputs. Fig. 25G may show the connections between a set of
structural units
and other building components.
[0125]
Exemplary Fig. 25H may show a set of sheathing units. A sheathing unit may
be sheet material that may be formed from a doubly-curved surface, and may
consist of an
ordered set of parts with shapes, sizes, and manufacturing data computed from
design inputs
by software. Manufacturing data may include cuts, holes, and markings on the
parts as well as
locations to connect a sheathing unit to other parts, units, or building
components. Parts of a
sheathing unit may be cut with a CNC machine.
[0126]
Exemplary Fig. 251, Fig. 25J, Fig. 25K may show sets of formwork units. A
formwork unit may be a part cut by a CNC machine from a thick sheet, such as
rigid foam, or
a thick sheet of a composite of laminated materials. One side of a formwork
unit part may be
cut with a CNC machine such that the cut surface may be parallel to one
surface of a masonry
wall, and where each masonry unit may be positioned at varying angles relative
to adjacent
masonry units. Reference graphical markings on the formwork unit may be used
as guides for
locating masonry units of standard sizes and may be used to communicate
dimensional data for
cutting of masonry units or may be used for calibrating the position of a
robotic masonry laying
machine in the physical 3D environment. This may reduce accrued error and
conflicts from
discrepancies between the designed virtual model of the wall elements and
adjustments
required to meet other physical architectural building components of other
construction
methods with varying degrees of accuracy. Similar to the structural units
shown in Fig. 25B,
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the rigid foam unit shown in Fig. 25J may be designed as a low level set
within a network of
sets, such as the full assembly of rigid foam units shown in Fig. 25K. In
addition to the
perimeter compound saw cuts, each course with markings for bricks as joint
types may be an
edge type used in the design of the unit modeled with software. Angles for the
compound CNC
saw cuts, and routing depths of the CNC milling machine shaping the rigid foam
unit may be
calculated after mapping the x- and y- coordinates of the unit object in the
flattened design
surface to the u- and v- coordinates of the three- dimensional design surface.
Parts of a foam
unit may be glued together with a CNC gluing machine.
[0127] Fig. 25L
may show a cross-section of the assembly of a building system. The
building system may be a combination of sets of units defined through design
inputs. A building
system may contain a set of structural units connected to one or more sets of
structural units,
sheathing units, and/or formwork units.
[0128]
Referring now to exemplary Fig. 25M, Fig. 25M may illustrate the connection
detail between non-parallel building components. A round tube of a structural
unit may be
connected to a second part, such as a sheathing unit, a formwork unit, or any
building
component. The normal surface vector at the point of connection with the
second part may not
be perpendicular to the center axis of the round tube.
[0129]
Referring now to exemplary Fig. 26, Fig. 26 may illustrate an alternate
embodiment of a splice joint. The splice joint in Fig. 26 may connect two
pieces of different
materials. The first part 2600 may contain a notch 2602 and a tab 2604. The
notch 2602 may
receive the tenon 2612 on piece 2610, and the tab may be inserted into the
corresponding tabbed
notch 2614. This joint may be used when it is desired that the material of
part 2600 is concealed.
[0130] The
following examples may illustrate a method for structuring data for solving
two- dimensional and three- dimensional design problems. The problem spaces
may be
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explored manually through an intuitive graphical user interface (the interface
may be web-
based) as well as automatically with generative design algorithms. Problem
spaces may be
structured as layered networks of sets where sets may represent design
elements, such as units,
peripherals of units, other design elements like empty space (required for
space planning), and
groupings of design elements. The features may show various methods or ways of
manipulating
the different dimensions of the units or sets. The following examples may
focus on altering just
one dimension, such as the width, for the sake of simplicity and illustration,
although it may be
contemplated that they may be applied to any other dimensions of the object,
such as the length,
the height or the depth, as desired. Structuring of the problem space in this
way may allow for
cohesion and consistency in modeled design solutions while the networks of
sets are generated
and edited. As a result, functions for generating and editing the sets may be
programed to be
called manually by a user through a design interface or automatically by
generative design
algorithms, such as a genetic algorithm. One or more of the set division, set
editing, and set
generation features and functions described below may be used in the
generation of a set as a
set generator function. In much the same way that a design professional may
provide
recommended design solutions as well as alternatives to a client, the
generative design
algorithm may present the customer (user of the software) with suggested
designs for
consideration. Because the underlying structure of the problem space may be
the same for both
manual and automatic generation and editing of design solutions, the client,
with limited design
experience with the problem space, may be directly engaged in the creative
design process.
[0131]
Referring now to exemplary Fig. 27A, 27B, and 27C, Fig. 27A may illustrate a
set and subsets as dimensional drawings and layered graphs. The dimensional
drawings 2702
may show the relative dimensional variables of the sets, such as height and
width. The layered
graph drawings 2704 may show the hierarchical data structures for each network
of sets. In this
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exemplary embodiment, the first set A may have two free dimensions, such as
height and width.
Further, there may be subsets on layers below set A, which may share one or
more dimensions
inherited from the parent set. They may also have one or more free dimensions
which may be
a fraction of the corresponding dimension of their shared parent set. In an
exemplary
embodiment, the sum of the free dimensions may equal the shared parent
dimensions. In the
exemplary embodiment illustrated in Fig. 27A, the heights of sets B, C, and D
are each a
fraction the height of set A, and their combined heights may equal the height
of set A. The
width of sets B, C, and D may be equal to the width of set A. Fig. 27A may
illustrate two layers
of ordered sets, where sets B, C, and D are subsets of set A. Fig. 27B may
illustrate an alternate
embodiment, where sets D and E are subsets of set A, and sets B and C are
subsets of set E,
which is a subset of set A. The heights of sets B and C are each a fraction
the height of set E,
and their combined heights may equal the height of set E. Sets B and C may be
characterized
as a third layer, since they are a subset of set E which is a subset of set A.
Exemplary Fig. 27C
may illustrate a configuration with four layers. In this exemplary embodiment,
sets F and G are
subsets of set C, which is a subset of set E, which is a subset of set A. The
widths of sets F and
G may be free dimensions; however, they may inherit their heights from set C.
[0132]
Referring now to exemplary Fig. 28, Fig. 28 may illustrate sets and subsets in
three dimensions. The sets and subsets may be modeled with a height, width,
and depth. The
set 2802 may contain a set A which may have 3 free dimensions. Set A may
further include
subsets B and C, as modeled by the layered graph 2804. Three- dimensional
subsets may have
one free dimension and two inherited dimensions. Sets B and C of the set 2802
may share the
width and depth of set A, while having a free height. In this exemplary
embodiment, the
combined height of subsets B and C is equal to the height of set A.
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[0133] The set
2806 may contain a third layer, in which subsets D and E may be subsets
of set B, as modeled by the layered graph 2808. The subsets D and E share a
height and depth
with set B, and their combined width may equal the width of set B. The set
2810 may contain
a fourth layer, in which subsets F and G are subsets of set D, which is a
subset of set B, which
is a subset of set A, as modeled by the layered graph 2812.
[0134]
Referring now to exemplary Fig. 29, Fig. 29 may illustrate an example of how
an algorithm may calculate a value range for a variable of a set. For example,
the algorithm
may determine a maximum and a minimum height, width, or depth of a dimension
of a set. In
an exemplary embodiment, the algorithm may use the total set width 2902 to
calculate a
maximum subset width 2904. Additionally, the algorithm may calculate a minimum
subset
width 2906. The determination of the maximum and minimum subset width may
allow the
algorithm to determine a maximum or minimum number of subsets each set can
hold.
[0135]
Referring now to exemplary Fig. 30, the implementation of a set editing
function may be illustrated. In this exemplary illustration, set A may have
three subsets, and
the user may add a fourth subset. It is understood that in this example and
all subsequent
examples of set editing functions and set generating functions, an automation
algorithm may
substitute for the user, where the parameters and decisions are
probabilistically or heuristically
determined. The user may click on the insertion position 3002 to select where
the additional
set is to be inserted. In this exemplary case, the user selected the insertion
position 3002
between sets C and D, and an additional set E was added. It may be
contemplated that the user
may have chosen one of any number of possible insertion points, such as the
point between
sets B and C. If the user attempts to insert a set in a dimension where the
maximum number of
sets has already been reached, an error message may appear to explain to the
user why the
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additional set may not be added. The algorithm may not add the additional set
if the sum of the
minimum widths for sets B, C, E, and D exceeds the width of set A.
[0136]
Referring now to exemplary Fig. 31, an exemplary set editing function may be
shown where a subset is removed from a set. The algorithm may take the subset
to remove as
the input. The user may select which subset is to be removed. In this
exemplary embodiment,
the user selected subset C to be removed. As a result, the algorithm removed
subset C and
increased the widths of subsets B and D so that their widths equal the width
of the parent set
A. Before removing set C, the algorithm may check if the maximum widths of the
remaining
sets B and D are equal to or greater than the width of set A. If the maximum
widths of the
remaining sets is less than that of the parent set, the selected subset may
not be removed.
Additionally, when a subset cannot be removed the algorithm may display an
error message to
inform the user of the anomaly.
[0137]
Referring now to exemplary Fig. 32, Fig. 32 may illustrate an example of a set
editing function where one free dimension of a subset may be changed. The user
may select a
subset to change and input a new subset dimension. In this exemplary
embodiment, sets B, C,
D, and E may be subsets of set A. The user may enter a new width for set B,
the width of set C
may be fixed, and the widths of sets D and E may be variable. The algorithm
may then calculate
new widths for sets D and E, while changing the width for set B corresponding
to the user
input. The difference between the old value for the width of set B and the new
value for the
width of set B may be proportionally divided between the variable sets, in
this case sets D and
E.
[0138]
Referring now to exemplary Fig. 33, Fig. 33 may illustrate an exemplary set
editing function where free dimensions of multiple subsets may be changed
simultaneously.
The user may select a set and may choose the dimensions of the subset to
alter. In this
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exemplary embodiment, the widths of sets B, C and D are represented as
fractions of the width
of set A, where their combined proportions equal 1Ø New width values of any
real number
are either assigned to the sets or are calculated by adding these new width
values to the previous
width values as shown in this example. The array of ordered values is then
normalized by the
algorithm to generate values for sets B, C and D that are proportions of set
A. In this exemplary
embodiment, the width of set B is decreased by .2, the width of set C is not
changed, and the
width of set D is increased by .4. The resultant ordered array of values for
sets B, C and D are
.3, .3, and .6. As shown in the exemplary embodiment, the normalized values
for the array of
values are .25 (width of set B), .25 (width of set C), and .5 (width of set
D). In another case,
the user may change the free dimensions of multiple subsets sequentially. In
this exemplary
embodiment, the user selected sets B and D, and then chose to reduce the width
of set B by .25
while increasing the width of set D by .3. The algorithm may then allocate any
remaining space
to the unselected variable widths, in this case the width of set C was reduced
by .05. The user
may select a ratio or proportion to reduce, for example by decreasing the
width of set B by .25
or 25% of the total width. Alternatively, the user may reduce the dimensions
directly, such as
by selecting an option to reduce the width of set B by .25 feet.
[0139]
Referring now to exemplary Fig. 34, Fig. 34 may illustrate an exemplary set
editing function where the widths of multiple sets within a network of sets
are made equal. The
user may select multiple sets, and the algorithm may automatically set the
network of sets to
have equal widths. In the exemplary embodiment illustrated in Fig. 34, the
user may select D,
E, and C, and the algorithm may allocate equal widths for each of the selected
sets.
[0140]
Referring now to exemplary Fig. 35, Fig. 35 may illustrate an exemplary set
editing function which may change the free dimension of a subset while the
position and width
of another subset of the same set is fixed. The function may take the set to
change and the new
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value for the set as inputs. In this exemplary embodiment, sets B, C, D, and E
are subsets of A,
and the position and width of set C is fixed. When the width of set D is
changed, the width of
set B may stay the same because altering the width of set B may change the
position of set C.
As a result, the width of set E is the sole dimension which is reduced to
compensate for the
extension of the width of set D.
[0141]
Referring now to exemplary Fig. 36, Fig. 36 may illustrate an exemplary set
editing function which may change a non-dimensional variable of a set. A user
may select a set
to change, and then may select a variable to change as well as the new type or
value of the
variable. In this exemplary embodiment, the type of material of set C is
changed.
[0142]
Referring now to exemplary Fig. 37, Fig. 37 may illustrate an exemplary set
editing function which may replace dimensional and/or non-dimensional
parameters of a set
with parameters copied from another set. In the exemplary embodiment
illustrated in Fig. 37,
the dimensions of set C, consisting of subsets E and F, are copied over to set
D. As a result, set
D may have the same subsets as set C, and may further include the same
materials, widths, and
heights. The algorithm may not copy all parameters and subsets from the
reference set to the
target set. The algorithm may copy as many subsets and parameters as possible.
For instance,
if the width of set D is fixed, the algorithm might copy subsets and their
materials and heights,
but not widths.
[0143]
Referring now to exemplary Fig. 38, Fig. 38 may illustrate an exemplary set
editing function which may change or swap the positions of sets within a
network. A user may
select one or more sets and select one or more new positions for those sets.
In the exemplary
embodiment illustrate by Fig. 38, the user selected sets C and D and switched
their positions
such that set C was now in the position set D previously occupied, and vice-
versa.
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[0144]
Referring now to exemplary Fig. 39, Fig. 39 may illustrate an exemplary set
editing function which may group neighboring sets. Multiple sets which are
near each other
may be selected by a user and may be grouped to become one set which may share
some
dimensions. In this specific exemplary embodiment, set C contains subsets E
and F, and set D
contains subsets G and H. Sets F and H are selected and grouped together, such
that they may
share the same height. Further, sets E and G may be selected and grouped
together such that
they share the same height.
[0145]
Referring now to exemplary Fig. 40, Fig. 40 may illustrate another exemplary
set editing function which may align the division between sets or subsets. A
user may select a
dividing line between two sets, and may select another dividing line to line
it up with. In the
exemplary embodiment illustrated in Fig. 40, the dividing line between sets D
and E is selected
and aligned with the dividing line between sets F and G.
[0146]
Referring now to exemplary Fig. 41, Fig. 41 may illustrate a graph
optimization
function. In this example, subset D was removed from set C. As a result, set C
had just one
subset, set E. The graph optimization function may then remove subset E since
it may be the
only remaining subset of set C, and its dimensions may equal those of set C.
[0147]
Referring now to exemplary Fig. 42, Fig. 42 may illustrate an exemplary set
editing function (one point crossover set generator function of a genetic
algorithm) which may
generate a new set by splitting two input sets and combining one portion of
the first input set
with a portion of a second input set. The function may take one input set, a
crossover point
from the first input set, a second input set, and a crossover point from the
second input set as
inputs. In this specific exemplary embodiment, the first input set (set A) may
have two ordered
subsets (sets B and C). Set C may have three ordered subsets D, E, and F. The
second input set
(set G) may have two ordered subsets (sets H and I). Sets H and I may each
have two ordered
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subsets. The first crossover point may be between neighboring sets D and E.
The second
crossover point may be between the neighboring sets J and K. The output may be
a new set, a
copy of set A, with ordered subsets (copies of sets B and C), where the copy
of set C has two
ordered subsets (copies of sets D and K).
[0148]
Referring now to exemplary Fig. 43, Fig. 43 may illustrate an example of a set
editing function (two point crossover set generator function of a genetic
algorithm) which may
generate a new set by splitting two input sets and combining portions of the
first input set with
portions of a second input set. In this exemplary embodiment, the function may
take one input
set, multiple crossover points from the first input set, a second input set,
and multiple crossover
points from the second input set as inputs. In this example, the first input
set (Set A) has four
ordered subsets (Sets B, C, D, & E), and the second input set (Set F) has
three ordered subsets
(Sets G, H, & I). Crossover points for the first set are between B & C and
Sets D & E. Crossover
points for the second set are between Sets H & I and after Set I. The output
may be a new set
(a copy of Set A) with ordered subsets (copies of Sets B, I, & E). Other
exemplary set generator
functions with more than two crossover points may be considered.
[0149]
Referring now to exemplary Fig. 44, Fig. 44 may illustrate an exemplary
kitchen
plan layout. The room for the kitchen design may have overall dimensions, such
as a length
4402 and a width 4404 (x, y), an open side 4406, three walls, and one window
in one of the
walls 4408. The kitchen design may include base cabinet units 4410, wall
cabinet units 4412,
an appliance 4414 and a sink 4416 along the wall with the window. It may also
include kitchen
island cabinets 4418, an aisle 4420 between the kitchen wall and kitchen
island, and aisles
between the kitchen island and side walls.
[0150]
Referring now to exemplary Fig. 45, Fig. 45 may illustrate an exemplary method
for generating the kitchen plan layout design shown in Fig. 44. The method may
generate and
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edit a network of sets, shown here as dimensional drawings. First, the overall
room may be
shown 4502 as set A, where the width may be equal to the x-dimension of the
space and the
height may be equal to the y-dimension of the space. Next, the space (Set A)
divided into three
zones 4504 (Sets B, C, & D as ordered subsets of Set A). In a next step, the
type parameter of
Set B (zone along the wall with the window) may be changed 4506, such as to
'Kitchen Wall'.
In a next exemplary step, a set, set D (zone next to the room edge open to
another space) in this
case, may be divided into three zones 4508 as ordered subsets (Sets E, F, &
G). Further, the
type parameter of Set F may be changed 4510, such as to 'Kitchen Island' in
this exemplary
embodiment. In a next exemplary step, new width parameters may be set 4512 for
the sets. In
this exemplary embodiment, the widths of sets E, F, & G were changed.
Alternatively, the
previous steps may be skipped by selecting a standard kitchen plan layout type
from a list of
standard pre-programed kitchen plan layouts.
[0151]
Referring now to exemplary Fig. 46, Fig. 46 may illustrate exemplary pre-
programmed subsets. These subsets may allow for completely pre-programmed
kitchen plan
layout types. By using pre-programmed kitchen plan layouts or sets, the user
may save time by
decreasing the number of required steps in generating a kitchen plan layout
design.
Additionally, the pre-programmed sets may be examples of room designs that may
be subsets
of networks of sets representing floor plan configurations of buildings. The
pre-programmed
kitchen plan layouts may have relative and standard free dimension parameters
that enable
conformity with the overall room dimensions of a set.
[0152]
Referring now to exemplary Fig. 47, Fig. 47 may illustrate an example of a
kitchen wall layout. The wall may have overall dimensions such as a width and
a height (x, z).
The wall may have one window of a user-defined size. The wall may include an
appliance,
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cabinet units, base units, a sink base cabinet unit with doors, two base
cabinet units with doors
and drawers, and a work area above the base cabinet units.
[0153]
Referring now to exemplary Fig. 48A and 48B, Fig. 48A and 48B may illustrate
an exemplary method for manually generating the kitchen wall design shown in
Fig. 47. Fig.
48A may illustrate the method using dimensional drawings, while Fig. 48B may
illustrate the
method using layered graphs. In an exemplary first step, the algorithm may
create a new set A
with a width equal to the x dimension of the space and a height equal to the z-
dimension of the
space 4802. Set A may be divided into ordered subsets, such as subsets B, C,
and D in the
example illustrated here. Set C may be a column with fixed position and width
parameters and
may be divided into two subsets, E and F. Set E may denote the window zone
with a fixed
height parameter. In a next exemplary step, additional appliances and cabinet
units may be
added 4804. In another exemplary step, columns may be added with wall units
and base units
4806. These may be added to the network of sets. In a next exemplary step,
wall units work
areas and base units may be grouped 4808. In a next exemplary step, doors,
drawers, and fixed
panels may be added to the network of sets 4810. In a final exemplary step,
the widths of doors
represented by sets b, c, and P may be made equal. The algorithm computes new
width values
for sets b, c, P, and K (parent set of sets b and c), so that widths of sets
b, c, and P are equal,
and the sum of the widths of sets P and K equal the width of their parent set,
set J.
[0154]
Referring now to exemplary Fig. 49, Fig. 49 may illustrate an exemplary method
for automatically generating a set by calling set editing functions. In this
example, components,
units, columns, and kitchen walls may be sets with ranges of dimensional and
non-dimensional
parameters particular to those set types. Components may be subsets of units,
and units may be
subsets of columns. Parameters for these sets may be randomly selected from
domains of
possible values. The probability that any one value within a range of possible
values may be
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selected may be weighted to increase the odds that some values may be selected
over others.
Optimal weights may be selected by the programmer of the algorithm, calculated
from variable
values entered by a user, or may be determined using machine learning
algorithms. In this
exemplary embodiment, a kitchen wall set may be generated using predetermined
overall
dimensions. The layered graphs of the kitchen wall may be normalized and
optimized for
efficient analysis and future set editing. Networks of sets may be
automatically generated using
heuristic algorithm(s), metaheuristic algorithm(s) and/or optimization
algorithm(s).
[0155]
Referring now to exemplary Fig. 50, Fig. 50 may illustrate an exemplary
kitchen
wall design systematically generated by the method described in Fig. 49. In
this example, some
of the weights used in the random selection of unit types and other parameters
may be
determined by user defined values such as the overall dimensions of the wall
and the required
number of appliances. Heuristics may be integrated to efficiently generate
acceptable design
solutions. For instance, Set G in this example may be a required appliance,
and only one
appliance may be allowed. When iterating through the subsets of Set A, the
probability that the
appliance will be added to any given subset is the index value of the subset
within the array of
sets divided by the number of subsets, guaranteeing the inclusion of the
appliance in the
network of sets. The algorithm may adjust selection weights throughout the
generation. For
example, when an appliance is added to the network of sets, the probability
another appliance
will be added may be adjusted to zero, guaranteeing the exclusion of solutions
with multiple
appliances.
[0156]
Referring now to exemplary Fig. 51, Fig. 51 may illustrate the utilization of
a
genetic algorithm for automatically generating and selecting set designs.
Following this
process, an initial population of individual sets may be automatically created
with initial set
generation function(s). Fitness scores for each individual set in the
population may be
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calculated. A fitness score may be calculated from multiple factors weighted
by user inputs,
such as design aesthetic and functional requirements. An example design
aesthetic may be the
selection of a vertical appearance, resulting in networks of sets with narrow
set proportions. In
the example shown in Fig. 50, a functional fitness score may be higher for
solutions with higher
calculated continuous work area lengths. Another fitness function may be cost,
when selected
set types represent physical products with variable amounts of material and
construction
complexities.
[0157]
Referring now to exemplary Fig. 52, Fig. 52 may illustrate an example of a
population of individuals with fitness scores. After calculating fitness
scores of the population,
the algorithm may decide to either end the process and return individual(s)
from the current
population, or generate a new population. Example factors for making this
decision may
include a limit on computing resource, a limit on number of generations, the
presence of
minimally viable design solution(s), or minimal differences in scores between
current and
previous populations. To generate new populations, the genetic algorithm may
follow a process
inspired by natural selection where a network of sets and parameters of the
sets in the network
may represent an individual's genotype, and the collection of units and their
parameters
associated with sets within the network of sets may represent the phenotype,
and where new
populations of networks of sets may be generated by selecting networks of sets
from the
previous generation. Each selection is probabilistically determined by the
fitness scores of the
phenotypes. The selected networks of sets and their parameters are modified
with crossover
and mutation operators, forming a new generation. In this example, the
crossover and mutation
operators of the genetic algorithm are the set generator and set editing
functions.
[0158]
Referring now to exemplary Fig. 53A and 53B, an implementation of a set
generator function by a genetic algorithm may be shown. The generation of a
kitchen wall set
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may come from one or more input sets. In this exemplary embodiment, the input
sets may be
selected from a population of sets. In this exemplary embodiment, the set
generator function is
a single point crossover function, similar to the set generator function
illustrated in Fig. 42,
where the crossover point of the first input set is between ordered sets D and
E, and the
crossover point of the second input set is between ordered sets f and g.
[0159]
Referring now to exemplary Fig. 54, Fig. 54 may illustrate an exemplary output
set as a mutation of an input set. The mutated version may be achieved with a
set editing
function selected by a genetic algorithm. In this example, the input set is
edited by grouping
the wall cabinet doors of the input (Sets M, N, U, V, d, & e) with the set
editing function
illustrated in Fig. 39, making the widths of these doors equal with the set
editing function
illustrated in Fig. 34, changing the number of drawers in a base cabinet (Set
L) with the set
editing function illustrated in Fig. 31, changing the widths of the doors of
the sink cabinet (Set
X) with the set editing function illustrated in Fig. 33, and changing the type
of a cabinet (Set
C) from a sink cabinet (fixed panel and two doors) to a base cabinet with one
door with the set
editing function illustrated in Fig. 36.
[0160]
Referring now to exemplary Fig. 55 is a method for creating and using the
interface for finding a solution to a problem in a two- dimensional or three-
dimensional
problem space structured as a network of sets. An exemplary problem space may
be the
coordination and design of custom cabinetry within a space, such as a kitchen.
While a cabinet
is a three- dimensional product, and a kitchen is a three- dimensional space,
the design of an
overall set of cabinets may be divided into coordinated two- dimensional
design problems
spaces (one plan and one or more elevations). A single cabinet, requiring the
design and
coordination of peripherals such as doors and drawers, may be another example
of a design
problem with a two- dimensional problem space.
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[0161] After
identifying a multi- dimensional design problem, a user interface for the
problem space may be constructed as a network of sets and functions for
generating and editing
the network of sets. With the interface, users with varying degrees of
experience with the
interface and knowledge of the problem space may decide to either manually
generate a
problem solution with design aids provided by the interface, or instruct the
software to
automatically generate a solution with minimal inputs. An exemplary solution
automatically
generated from minimal inputs may be a cabinet design with doors and drawers
generated from
user inputs, such as size and volume or other dimensional as well as non-
dimensional
requirements. Software may automatically determine more detailed design
requirements from
minimal inputs provided by the user with a question-air form or verbal
instructions. Exemplary
verbal instructions may be, "I need a cabinet to hold 3 large pots, 10 small
plates, and knives"
or "I want a kitchen with horizontal lines." Using natural language processing
algorithms along
with heuristics and/or machine learning algorithms, the software may
automatically determine
or approximate unit proportions as well as volumetric and area requirements
from these inputs,
and use these requirements as fitness criteria in automatically generating an
overall kitchen
and/or cabinet design solution.
[0162] If the
user is not satisfied with the solution, the user may decide to either
manually edit the solution with design aids provided by the interface, or
instruct the software
to automatically edit the solution with additional inputs. Machine learning
algorithms (such as
object recognition algorithms) may be trained to recognize overall kitchen
styles and aid in the
generation of solutions for certain types of quantitative as well as
qualitative inputs. For
instance a user may instruct the software to automatically generate a kitchen
design that fits
their quantitative requirements in addition to having a qualitative appearance
similar to another
kitchen or other kitchens.
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[0163] Other
exemplary interfaces with the previous mentioned features for two-
dimensional design problem spaces may include virtual and physical media with
organized
design elements, such as promotional flyers, stationary, and webpage layouts.
These exemplary
interfaces are more desirable than current technologies, where users are only
able to select from
a curated set of standard templates.
[0164] An
exemplary three- dimensional design problem is a whole building design
with multiple levels that require design coordination between levels. The
problem space for
this design problem may be constructed as a three- dimensional network of
sets. In the
automatic generation of a whole building design, the software may perform
whole building
analysis in determining fitness. Exemplary analyses of a building include a
building's relative
size and position to other site elements (roads, other buildings, shading
element such trees, and
views), life safety analysis, code compliance, and energy analysis.
[0165] The
foregoing description and accompanying figures illustrate the principles,
preferred embodiments and modes of operation of the invention. However, the
invention
should not be construed as being limited to the particular embodiments
discussed above.
Additional variations of the embodiments discussed above will be appreciated
by those skilled
in the art (for example, features associated with certain configurations of
the invention may
instead be associated with any other configurations of the invention, as
desired).
[0166]
Therefore, the above-described embodiments should be regarded as illustrative
rather than restrictive. Accordingly, it should be appreciated that variations
to those
embodiments can be made by those skilled in the art without departing from the
scope of the
invention as defined by the following claims.
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